Multiple The right time Group fashion making use of Apache Trigger and Facebook Visionary

#datascience #machinelearning #timeseries

This video is part of Time Series playlist here –

One major challenge with time series in real world is dealing with multiple time series, Be it retailers who have millions of product and every product having different sales cycle or manufacturing industry dealing with hundreds of machinery. In such cases we need systems and solution that can help distribute time series model building across distributed nodes to enable high parallelism. In this video we will see how we can use facebook prophet to model and Apache Spark to distribute across multiple nodes

Gretl Particular tutorial six: Fashion and Conjecturing Moment in time Show Statistics

In this video we run a linear regression on a time series dataset with time trend and seasonality dummies. Then, we perform and evaluate the accuracy of an in-sample forecast, as well as perform an out-of-sample (i.e., into the future) forecast.

00:00 Introduction
00:12 What we will do in this Video
00:40 Data
01:14 Glimpse Data in Excel
01:46 Load Data in Gretl
03:20 Plot Time Series
03:54 Create Additional Variables
04:38 Run Model with All Data
05:34 In-Sample Forecast
06:40 Evaluating Quality of In-Sample Forecast
10:37 Out-of-Sample Forecast

Sensing and Fashion The right time Group Gene Term with the use of Come and DREM

2015 Network Analysis Short Course
– Systems Biology Analysis Methods for Genomic Data

Speaker: Jason Ernst, UCLA

The goal of the network analysis workshop is to familiarize researchers with network methods and software for integrating genomic data sets with complex phenotype data. Students will learn how to integrate disparate data sets (genetic variation, gene expression, epigenetic, protein interaction networks, complex phenotypes, gene ontology information) and use networks for identifying disease genes, pathways and key regulators.